AMiGA: Software for Automated Analysis of Microbial Growth Assays

Emerging Clostridioides difficile ribotypes have divergent metabolic phenotypes

Clostridioides difficile is a gram-positive spore-forming pathogen that commonly causes diarrheal infections in the developed world. Although C. difficile is a genetically diverse species, certain ribotypes are overrepresented in human infections. It is unknown if metabolic adaptations are essential for the emergence of these epidemic ribotypes. Here, we tested carbon substrate utilization by 88 C. difficile isolates and looked for differences in growth between 22 ribotypes. By profiling clinical isolates, we assert that C. difficile is a generalist species capable of growing on a variety of carbon substrates. Further, C. difficile strains clustered by phylogenetic relationship and displayed ribotype-specific and clade-specific metabolic capabilities. Surprisingly, we observed that two emerging lineages, ribotypes 023 and 255, have divergent metabolic phenotypes. In addition, although C. difficile Clade 5 is the most evolutionary distant clade and often detected in animals, it displayed more robust growth on simple dietary sugars than Clades 1-4. Altogether, our results corroborate the generalist metabolic strategy of C. difficile and demonstrate lineage-specific metabolic capabilities. In addition, our approach can be adapted to the study of additional pathogens to ascertain their metabolic niches in the gut.

IMPORTANCE

The gut pathogen Clostridioides difficile utilizes a wide range of carbon sources. Microbial communities can be rationally designed to combat C. difficile by depleting its preferred nutrients in the gut. However, C. difficile is genetically diverse with hundreds of identified ribotypes and most of its metabolic studies were performed with lab-adapted strains. Here, we profiled carbon metabolism by a myriad of C. difficile clinical isolates. While the metabolic capabilities of these isolates clustered by their genetic lineage, we observed surprising metabolic divergence between two emerging lineages. We also found that the most genetically distant clade grew robustly on simple dietary sugars, posing intriguing questions about the adaptation of C. difficile to the human gut. Altogether, our results underscore the importance of considering the metabolic diversity of pathogens in the study of their evolution and the rational design of therapeutic interventions.

Fitness factor genes conserved within the multi-species core genome of Gram-negative Enterobacterales species contribute to bacteremia pathogenesis

There is a critical gap in knowledge about how Gram-negative bacterial pathogens, using survival strategies developed for other niches, cause lethal bacteremia. Facultative anaerobic species of the Enterobacterales order are the most common cause of Gram-negative bacteremia, including Escherichia coli, Klebsiella pneumoniae, Serratia marcescens, Citrobacter freundii, and Enterobacter hormaechei. Bacteremia often leads to sepsis, a life-threatening organ dysfunction resulting from unregulated immune responses to infection. Despite a lack of specialization for this host environment, Gram-negative pathogens cause nearly half of bacteremia cases annually. Based on our existing Tn-Seq fitness factor data from a murine model of bacteremia combined with comparative genomics of the five Enterobacterales species above, we prioritized 18 conserved fitness genes or operons for further characterization. Mutants were constructed for all genes in all five species. Each mutant was used to cochallenge C57BL/6 mice via tail vein injection along with each respective wild-type strain to determine competitive indices for each fitness gene. Five fitness factor genes, when mutated, attenuated mutants in four or five species in the spleen and liver (tatC, ruvA, gmhB, wzxE, arcA). Five additional fitness factor genes or operons were validated as outcompeted by wild-type in three, four, or five bacterial species in the spleen (xerC, prc, apaGH, atpG, aroC). Overall, 17 of 18 fitness factor mutants were attenuated in at least one species in the spleen or liver. Together, these findings allow for the development of a model of bacteremia pathogenesis that may include future targets of therapy against bloodstream infections.

gcplyr: an R package for microbial growth curve data analysis

BACKGROUND

Characterization of microbial growth is of both fundamental and applied interest. Modern platforms can automate collection of high-throughput microbial growth curves, necessitating the development of computational tools to handle and analyze these data to produce insights.

RESULTS

To address this need, here I present a newly-developed R package: gcplyr. gcplyr can flexibly import growth curve data in common tabular formats, and reshapes it under a tidy framework that is flexible and extendable, enabling users to design custom analyses or plot data with popular visualization packages. gcplyr can also incorporate metadata and generate or import experimental designs to merge with data. Finally, gcplyr carries out model-free (non-parametric) analyses. These analyses do not require mathematical assumptions about microbial growth dynamics, and gcplyr is able to extract a broad range of important traits, including growth rate, doubling time, lag time, maximum density and carrying capacity, diauxie, area under the curve, extinction time, and more.

CONCLUSIONS

gcplyr makes scripted analyses of growth curve data in R straightforward, streamlines common data wrangling and analysis steps, and easily integrates with common visualization and statistical analyses.

Evaluating virulence features of Acinetobacter baumannii resistant to polymyxin B

The increasing resistance to polymyxins in Acinetobacter baumannii has made it even more urgent to develop new treatments. Anti-virulence compounds have been researched as a new solution. Here, we evaluated the modification of virulence features of A. baumannii after acquiring resistance to polymyxin B. The results showed lineages attaining unstable resistance to polymyxin B, except for Ab7 (A. baumannii polymyxin B resistant lineage), which showed stable resistance without an associated fitness cost. Analysis of virulence by a murine sepsis model indicated diminished virulence in Ab7 (A. baumannii polymyxin B resistant lineage) compared with Ab0 (A. baumannii polymyxin B susceptible lineage). Similarly, downregulation of virulence genes was observed by qPCR at 1 and 3 h of growth. However, an increase in bauE, abaI, and pgAB expression was observed after 6 h of growth. Comparison analysis of Ab0, Ab7, and Pseudomonas aeruginosa suggested no biofilm formation by Ab7. In general, although a decrease in virulence was observed in Ab7 when compared with Ab0, some virulence feature that enables infection could be maintained. In light of this, virulence genes bauE, abaI, and pgAB showed a potential relevance in the maintenance of virulence in polymyxin B-resistant strains, making them promising anti-virulence targets.

The role of the universal sugar transport system components PtsI (EI) and PtsH (HPr) in Enterococcus faecium

Vancomycin-resistant enterococci (VRE) pose a serious threat to public health because of their limited treatment options. Therefore, there is an increasing need to identify novel targets to develop new drugs. Here, we examined the roles of the universal PTS components, PtsI and PtsH, in Enterococcus faecium to determine their roles in carbon metabolism, biofilm formation, stress response, and the ability to compete in the gastrointestinal tract. Clean deletion of ptsHI resulted in a significant reduction in the ability to import and metabolize simple sugars, attenuated growth rate, reduced biofilm formation, and decreased competitive fitness both in vitro and in vivo. However, no significant difference in stress survival was observed when compared with the wild type. These results suggest that targeting universal or specific PTS may provide a novel treatment strategy by reducing the fitness of E. faecium.

Wildfire Ashes from the Wildland-Urban Interface Alter Vibrio vulnificus Growth and Gene Expression

Climate change-induced stressors are contributing to the emergence of infectious diseases, including those caused by marine bacterial pathogens such as Vibrio spp. These stressors alter Vibrio temporal and geographical distribution, resulting in increased spread, exposure, and infection rates, thus facilitating greater Vibrio-human interactions. Concurrently, wildfires are increasing in size, severity, frequency, and spread in the built environment due to climate change, resulting in the emission of contaminants of emerging concern. This study aimed to understand the potential effects of urban interface wildfire ashes on Vibrio vulnificus (V. vulnificus) growth and gene expression using transcriptomic approaches. V. vulnificus was exposed to structural and vegetation ashes and analyzed to identify differentially expressed genes using the HTSeq-DESeq2 strategy. Exposure to wildfire ash altered V. vulnificus growth and gene expression, depending on the trace metal composition of the ash. The high Fe content of the vegetation ash enhanced bacterial growth, while the high Cu, As, and Cr content of the structural ash suppressed growth. Additionally, the overall pattern of upregulated genes and pathways suggests increased virulence potential due to the selection of metal- and antibiotic-resistant strains. Therefore, mixed fire ashes transported and deposited into coastal zones may lead to the selection of environmental reservoirs of Vibrio strains with enhanced antibiotic resistance profiles, increasing public health risk.

Novel automated antifungal susceptibility testing system for yeasts based on dual-detection algorithm of turbidimetry and colorimetry

Introduction. The increasing prevalence and growing resistance of fungi present a significant peril to public health. There are only four classes of antifungal medicines available today, and few candidates are in clinical trials.Hypothesis/Gap Statement. Rapid and sensitive diagnostic techniques are lacking for most fungal pathogens, and those that do exist are expensive or hard to obtain.Aim. This study aimed to evaluate the feasibility of a novel automated antifungal susceptibility testing system, Fungus AST, in comparison to the broth microdilution method (BMD) recommended by the Clinical and Laboratory Standards Institute (CLSI).Methodology. A total of 101 clinical Candida spp. isolates were collected from the Zengcheng Branch of Nanfang Hospital and subjected to antifungal susceptibility testing. Antifungal susceptibility was assessed using the Fungus AST method and the BMD.Results. In this study, we introduce a novel automated antifungal susceptibility testing system, Fungus AST, which detects the turbidity and/or colour intensity of microdilution wells using a four-wavelength detection technology in real time and is designed to match the growth characteristics of strains over time. Based on our analysis, all reportable ranges of Fungus AST were suitable for clinical fungal isolates in PR China. Within ±twofold dilutions, reproducibility was 100 %. Considering the BMD as a referenced method, ten antifungal agents (anidulafungin, caspofungin, micafungin, fluconazole, voriconazole, posaconazole, itraconazole, amphotericin B, 5-flucytosine and nystatin) showed an essential agreement of >95 %. The category agreement of five antifungal agents (anidulafungin, caspofungin, micafungin, fluconazole and voriconazole) was excellent at >90 %. One Candida albicans isolate and voriconazole showed a major error (ME) (1.7 %), and no other ME or very ME agents were found.Conclusion. Given the above, it can be argued that the utilization of Fungus AST is a discretionary automated approach. More improvements are needed in Fungus AST compared to the BMD system for a wider range of clinical isolates, including different types of fungi.

Machine learning identifies key metabolic reactions in bacterial growth on different carbon sources

Carbon source-dependent control of bacterial growth is fundamental to bacterial physiology and survival. However, pinpointing the metabolic steps important for cell growth is challenging due to the complexity of cellular networks. Here, the elastic net model and multilayer perception model that integrated genome-wide gene-deletion data and simulated flux distributions were constructed to identify metabolic reactions beneficial or detrimental to Escherichia coli grown on 30 different carbon sources. Both models outperformed traditional in silico methods by identifying not just essential reactions but also nonessential ones that promote growth. They successfully predicted metabolic reactions beneficial to cell growth, with high convergence between the models. The models revealed that biosynthetic pathways generally promote growth across various carbon sources, whereas the impact of energy-generating pathways varies with the carbon source. Intriguing predictions were experimentally validated for findings beyond experimental training data and the impact of various carbon sources on the glyoxylate shunt, pyruvate dehydrogenase reaction, and redundant purine biosynthesis reactions. These highlight the practical significance and predictive power of the models for understanding and engineering microbial metabolism.

BactEXTRACT: an R Shiny app to quickly extract, plot and analyse bacterial growth and gene expression data

To streamline the analysis and visualization of bacterial growth and gene expression data obtained by microtitre plate readers, we developed BactEXTRACT, an intuitive, easy-to-use R Shiny application. BactEXTRACT simplifies the transition from raw optical density, fluorescence and luminescence measurements to publication-ready plots. This package offers a user-friendly interface that reduces the complexity involved in growth curve and gene expression analysis and is generally applicable. BactEXTRACT is available at https://veeninglab.com/bactextract.

Roles of crrAB two-component regulatory system in Klebsiella pneumoniae: growth yield, survival in initial colistin treatment stage, and virulence

OBJECTIVES

Alternation of the colistin resistance-regulating two-component regulatory system (crrAB) is a colistin-resistance mechanism in Klebsiella pneumoniae (K. pneumoniae), but its role in bacteria is not fully understood.

METHODS

Twelve colistin-susceptible K. pneumoniae clinical isolates were included in this study: six crrAB-positive and six crrAB-negative. We deleted the crrAB genes from two crrAB-positive isolates and complemented them. We measured the growth yields by determining growth curves in lysogeny broth and minimal media with or without Fe2+. In vitro selection rates for colistin resistance were determined by exposure to colistin, and survival rates against high concentrations of colistin (20 mg/L) at the early stage of growth (20 min) were investigated. Virulence was determined using a serum bactericidal assay and Galleria mellonella larval infection.

RESULTS

The presence of crrAB was not associated with colistin resistance and did not increase the in vitro selection rate of colistin resistance after exposure. The growth yield of crrAB-positive isolates was higher in lysogeny broth media and increased when Fe2+ was added to minimal media. The crrAB-positive isolates showed higher survival rates in the early stages of exposure to high colistin concentrations. Decreased serum resistance was identified in the crrAB-deleted mutants. More G. mellonella larvae survived when infected by crrAB-deleted mutants, and higher survival rates of bacteria were identified within the larvae infected with wild-type than crrAB-deletant isolates.

CONCLUSION

Through rapid response to external signals, crrAB would provide advantages for K. pneumoniae survival by increasing the final growth yield and initial survival against colistin treatment. This may partly contribute to the bacterial virulence.

Parsley: a web app for parsing data from plate readers

SUMMARY

As demand for the automation of biological assays has increased over recent years, the range of measurement types implemented by multiwell plate readers has broadened and the list of published software packages that caters to their analysis has grown. However, most plate readers export data in esoteric formats with little or no metadata, while most analytical software packages are built to work with tidy data accompanied by associated metadata. 'Parser' functions are therefore required to prepare raw data for analysis. Such functions are instrument- and data type-specific, and to date, no generic tool exists that can parse data from multiple data types or multiple plate readers, despite the potential for such a tool to speed up access to analysed data and remove an important barrier for less confident coders. We have developed the interactive web application, Parsley, to bridge this gap. Unlike conventional programmatic parser functions, Parsley makes few assumptions about exported data, instead employing user inputs to identify and extract data from data files. In doing so, it is designed to enable any user to parse plate reader data and can handle a wide variety of instruments (10+) and data types (53+). Parsley is freely available via a web interface, enabling access to its unique plate reader data parsing functionality, without the need to install software or write code.

AVAILABILITY AND IMPLEMENTATION

The Parsley web application can be accessed at: https://gbstan.shinyapps.io/parsleyapp/. The source code is available at: https://github.com/ec363/parsleyapp and is archived on Zenodo: https://zenodo.org/records/10011752.

Interspecies interactions determine growth dynamics of biopolymer-degrading populations in microbial communities

Microbial communities perform essential ecosystem functions such as the remineralization of organic carbon that exists as biopolymers. The first step in mineralization is performed by biopolymer degraders, which harbor enzymes that can break down polymers into constituent oligo- or monomeric forms. The released nutrients not only allow degraders to grow, but also promote growth of cells that either consume the degradation products, i.e., exploiters, or consume metabolites released by the degraders or exploiters, i.e., scavengers. It is currently not clear how such remineralizing communities assemble at the microscale-how interactions between the different guilds influence their growth and spatial distribution, and hence the development and dynamics of the community. Here, we address this knowledge gap by studying marine microbial communities that grow on the abundant marine biopolymer alginate. We used batch growth assays and microfluidics coupled to time-lapse microscopy to quantitatively investigate growth and spatial distribution of single cells. We found that the presence of exploiters or scavengers alters the spatial distribution of degrader cells. In general, exploiters and scavengers-which we collectively refer to as cross-feeder cells-slowed down the growth of degrader cells. In addition, coexistence with cross-feeders altered the production of the extracellular enzymes that break down polymers by degrader cells. Our findings reveal that ecological interactions by nondegrading community members have a profound impact on the functions of microbial communities that remineralize carbon biopolymers in nature.

Recruitment of a Middling Promiscuous Enzyme Drives Adaptive Metabolic Evolution in Escherichia coli

A key step in metabolic pathway evolution is the recruitment of promiscuous enzymes to perform new functions. Despite the recognition that promiscuity is widespread in biology, factors dictating the preferential recruitment of one promiscuous enzyme over other candidates are unknown. Escherichia coli contains four sugar kinases that are candidates for recruitment when the native glucokinase machinery is deleted-allokinase (AlsK), manno(fructo)kinase (Mak), N-acetylmannosamine kinase (NanK), and N-acetylglucosamine kinase (NagK). The catalytic efficiencies of these enzymes are 103- to 105-fold lower than native glucokinases, ranging from 2,400 M-1 s-1 for the most active candidate, NagK, to 15 M-1 s-1 for the least active candidate, AlsK. To investigate the relationship between catalytic activities of promiscuous enzymes and their recruitment, we performed adaptive evolution of a glucokinase-deficient E. coli strain to restore glycolytic metabolism. We observed preferential recruitment of NanK via a trajectory involving early mutations that facilitate glucose uptake and amplify nanK transcription, followed by nonsynonymous substitutions in NanK that enhance the enzyme's promiscuous glucokinase activity. These substitutions reduced the native activity of NanK and reduced organismal fitness during growth on an N-acetylated carbon source, indicating that enzyme recruitment comes at a cost for growth on other substrates. Notably, the two most active candidates, NagK and Mak, were not recruited, suggesting that catalytic activity alone does not dictate evolutionary outcomes. The results highlight our lack of knowledge regarding biological drivers of enzyme recruitment and emphasize the need for a systems-wide approach to identify factors facilitating or constraining this important adaptive process.

Antibiotics promote intestinal growth of carbapenem-resistant Enterobacteriaceae by enriching nutrients and depleting microbial metabolites

The intestine is the primary colonisation site for carbapenem-resistant Enterobacteriaceae (CRE) and serves as a reservoir of CRE that cause invasive infections (e.g. bloodstream infections). Broad-spectrum antibiotics disrupt colonisation resistance mediated by the gut microbiota, promoting the expansion of CRE within the intestine. Here, we show that antibiotic-induced reduction of gut microbial populations leads to an enrichment of nutrients and depletion of inhibitory metabolites, which enhances CRE growth. Antibiotics decrease the abundance of gut commensals (including Bifidobacteriaceae and Bacteroidales) in ex vivo cultures of human faecal microbiota; this is accompanied by depletion of microbial metabolites and enrichment of nutrients. We measure the nutrient utilisation abilities, nutrient preferences, and metabolite inhibition susceptibilities of several CRE strains. We find that CRE can use the nutrients (enriched after antibiotic treatment) as carbon and nitrogen sources for growth. These nutrients also increase in faeces from antibiotic-treated mice and decrease following intestinal colonisation with carbapenem-resistant Escherichia coli. Furthermore, certain microbial metabolites (depleted upon antibiotic treatment) inhibit CRE growth. Our results show that killing gut commensals with antibiotics facilitates CRE colonisation by enriching nutrients and depleting inhibitory microbial metabolites.

High-throughput metabolomics for the design and validation of a diauxic shift model

Saccharomyces cerevisiae is a very well studied organism, yet ∼20% of its proteins remain poorly characterized. Moreover, recent studies seem to indicate that the pace of functional discovery is slow. Previous work has implied that the most probable path forward is via not only automation but fully autonomous systems in which active learning is applied to guide high-throughput experimentation. Development of tools and methods for these types of systems is of paramount importance. In this study we use constrained dynamical flux balance analysis (dFBA) to select ten regulatory deletant strains that are likely to have previously unexplored connections to the diauxic shift. We then analyzed these deletant strains using untargeted metabolomics, generating profiles which were then subsequently investigated to better understand the consequences of the gene deletions in the metabolic reconfiguration of the diauxic shift. We show that metabolic profiles can be utilised to not only gaining insight into cellular transformations such as the diauxic shift, but also on regulatory roles and biological consequences of regulatory gene deletion. We also conclude that untargeted metabolomics is a useful tool for guidance in high-throughput model improvement, and is a fast, sensitive and informative approach appropriate for future large-scale functional analyses of genes. Moreover, it is well-suited for automated approaches due to relative simplicity of processing and the potential to make massively high-throughput.

Modeling pH and Temperature Effects as Climatic Hazards in Vibrio Vulnificus and Vibrio Parahaemolyticus Planktonic Growth and Biofilm Formation

Climate-induced stressors, such as changes in temperature, salinity, and pH, contribute to the emergence of infectious diseases. These changes alter geographical constraint, resulting in increased Vibrio spread, exposure, and infection rates, thus facilitating greater Vibrio-human interactions. Multiple efforts have been developed to predict Vibrio exposure and raise awareness of health risks, but most models only use temperature and salinity as prediction factors. This study aimed to better understand the potential effects of temperature and pH on V. vulnificus and V. parahaemolyticus planktonic and biofilm growth. Vibrio strains were grown in triplicate at 25°, 30°, and 37°C in 96 well plates containing Modified Seawater Yeast Extract modified with CaCl₂ at pH's ranging from 5 to 9.6. AMiGA software was used to model growth curves using Gaussian process regression. The effects of temperature and pH were evaluated using randomized complete block analysis of variance, and the growth rates of V. parahaemolyticus and V. vulnificus were modeled using the interpolation fit on the MatLab Curve Fitting Toolbox. Different optimal conditions involving temperature and pH were observed for planktonic and biofilm Vibrio growth within- and between-species. This study showed that temperature and pH factors significantly affect Vibrio planktonic growth rates and V. parahaemolyticus biofilm formation. Therefore, pH effects must be added to the Vibrio growth modeling efforts to better predict Vibrio risk in estuarine and coastal zones that can potentially experience the cooccurrence of Vibrio and harmful algal bloom outbreak events.

Towards high-throughput screening (HTS) of polyhydroxyalkanoate (PHA) production via Fourier transform infrared (FTIR) spectroscopy of Halomonas sp. R5-57 and Pseudomonas sp. MR4-99

High-throughput screening (HTS) methods for characterization of microbial production of polyhydroxyalkanoates (PHA) are currently under investigated, despite the advent of such systems in related fields. In this study, phenotypic microarray by Biolog PM1 screening of Halomonas sp. R5-57 and Pseudomonas sp. MR4-99 identified 49 and 54 carbon substrates to be metabolized by these bacteria, respectively. Growth on 15 (Halomonas sp. R5-57) and 14 (Pseudomonas sp. MR4-99) carbon substrates was subsequently characterized in 96-well plates using medium with low nitrogen concentration. Bacterial cells were then harvested and analyzed for putative PHA production using two different Fourier transform infrared spectroscopy (FTIR) systems. The FTIR spectra obtained from both strains contained carbonyl-ester peaks indicative of PHA production. Strain specific differences in the carbonyl-ester peak wavenumber indicated that the PHA side chain configuration differed between the two strains. Confirmation of short chain length PHA (scl-PHA) accumulation in Halomonas sp. R5-57 and medium chain length PHA (mcl-PHA) in Pseudomonas sp. MR4-99 was done using Gas Chromatography-Flame Ionization Detector (GC-FID) analysis after upscaling to 50 mL cultures supplemented with glycerol and gluconate. The strain specific PHA side chain configurations were also found in FTIR spectra of the 50 mL cultures. This supports the hypothesis that PHA was also produced in the cells cultivated in 96-well plates, and that the HTS approach is suitable for analysis of PHA production in bacteria. However, the carbonyl-ester peaks detected by FTIR are only indicative of PHA production in the small-scale cultures, and appropriate calibration and prediction models based on combining FTIR and GC-FID data needs to be developed and optimized by performing more extensive screenings and multivariate analyses.

Transcriptomic Analysis Reveals That Municipal Wastewater Effluent Enhances Vibrio vulnificus Growth and Virulence Potential

Vibrio vulnificus is an opportunistic pathogen indigenous to estuarine and marine environments and associated with aquatic organisms. Vibrio vulnificus is of utmost importance because it causes 95% of the seafood-related deaths in the United States due to rapid progression of septicemia. Changes in environmental parameters associated with climate change and coastal population expansion are altering geographical constraints, resulting in increased Vibrio spread, exposure, and rates of infection. In addition, coastal population expansion is resulting in increased input of treated municipal sewage into areas that are also experiencing increased Vibrio proliferation. This study aimed to better understand the influence of treated sewage effluent on effluent-receiving microbial communities using Vibrio as a model of an opportunistic pathogen. Integrated transcriptomic approaches were used to analyze the changes in overall gene expression of V. vulnificus NBRC 15645 exposed to wastewater treatment plant (WWTP) effluent for a period of 6h using a modified seawater yeast extract media that contained 0, 50, and 100% filtered WWTP effluent. RNA-seq reads were mapped, annotated, and analyzed to identify differentially expressed genes using the Pathosystems Resource Integration Center analysis tool. The study revealed that V. vulnificus responds to wastewater effluent exposure by activating cyclic-di-GMP-influenced biofilm development. Also, genes involved in crucial functions, such as nitrogen metabolism and bacterial attachment, were upregulated depending on the presence of treated municipal sewage. This altered gene expression increased V. vulnificus growth and proliferation and enhanced genes and pathways involved in bacterial survival during the early stages of infection in a host. These factors represent a potential public health risk due to exposure to environmental reservoirs of potentially Vibrio strains with enhanced virulence profiles in coastal areas.